Genomewide patterns of variation in genetic diversity are shared among populations, species and higher‐order taxa

Abstract

Genomewide screens of genetic variation within and between populations can reveal signatures of selection implicated in adaptation and speciation. Genomic regions with low genetic diversity and elevated differentiation reflective of locally reduced effective population sizes (N ) are candidates for barrier loci contributing to population divergence. Yet, such candidate genomic regions need not arise as a result of selection promoting adaptation or advancing reproductive isolation. Linked selection unrelated to lineage-specific adaptation or population divergence can generate comparable signatures. It is challenging to distinguish between these processes, particularly when diverging populations share ancestral genetic variation. In this study, we took a comparative approach using population assemblages from distant clades assessing genomic parallelism of variation in N . Utilizing population-level polymorphism data from 444 resequenced genomes of three avian clades spanning 50 million years of evolution, we tested whether population genetic summary statistics reflecting genomewide variation in N would covary among populations within clades, and importantly, also among clades where lineage sorting has been completed. All statistics including population-scaled recombination rate (ρ), nucleotide diversity (π) and measures of genetic differentiation between populations (F , PBS, d ) were significantly correlated across all phylogenetic distances. Moreover, genomic regions with elevated levels of genetic differentiation were associated with inferred pericentromeric and subtelomeric regions. The phylogenetic stability of diversity landscapes and stable association with genomic features support a role of linked selection not necessarily associated with adaptation and speciation in shaping patterns of genomewide heterogeneity in genetic diversity.

Background selection and FST: Consequences for detecting local adaptation

“…In agreement with previous works (e.g. Charlesworth, ; Elyashiv et al, ; Messer & Petrov, ; Nordborg et al, ; Vijay et al, ; Zeng & Charlesworth, ), we show that background selection reduces genetic diversity, both within and among populations. The magnitude of this effect is very similar to previous realistic simulations (Messer & Petrov, ).…”

“…This is consistent with the results of our simulations. This result is in agreement with Vijay et al () who reported a strong correlation between H S and d XY when F ST is low ( F ST ≈ 0.02), but this correlation breaks down when studying more distantly related populations ( F ST ≈ 0.3).…”

“…Recently, evidence of a correlation between recombination rate and F ST has been interpreted as likely being caused by deleterious mutations rather than positive selection, whether the divergence between populations is very high (e.g. Cruickshank & Hahn, ), moderately high (Vijay et al, ) or moderately low (Torres et al, ). Here we showed the BGS is unlikely to explain all of these correlations between F ST and recombination rate, especially in cases with relatively low divergence among populations.…”

Coupling, Reinforcement, and Speciation

“…In agreement with this, cases have been documented of pleiotropy (reviewed in Servedio et al 2011) or of barrier loci falling in regions of reduced recombination (reviewed in Hoffmann and Rieseberg 2008;Faria and Navarro 2010). There is also increasing evidence for clustered genetic architectures of differentiation (reviewed in Wolf and Ellegren 2017) and reproductive isolation (e.g., Merrill et al 2011;Smadja et al 2012;Hermann et al 2013). Theoretical models have started to explore some possible mechanisms generating or favoring these clustered architectures (i.e., divergence hitchhiking [Feder et al 2012b;Flaxman et al 2013Flaxman et al , 2014Yeaman et al 2016]; chromosomal rearrangements [Yeaman 2013]; erosion from secondary contact [Yeaman et al 2016]; stochastic loss and gain of local genomic differentiation [Rafajlovic et al 2016]), but testing these scenarios with empirical data remains challenging.…”

“…This approach can help to reconstruct how genomic differentiation and coupling among barrier effects progress during speciation, assess whether the evolution of coupling and genome congealing (Barton 1983;Flaxman et al 2013 of chromosomal linkage and recombination rate variation in the evolution of coupling (e.g., Gagnaire et al 2013;Nadeau et al 2013;Burri et al 2015;Feulner et al 2015). Comparisons among examples with different overall barriers and different combinations of barrier effects, as well as comparative analyses of replicated and independent events of contact in a given system can also help this reconstruction (e.g., Nadeau et al 2014;Vijay et al 2017). In general, it will be important to identify more systems offering multiple hybrid zones to compare situations where coupling may not be at the same stage across the distribution range (e.g., in common voles [Beysard and Heckel 2014], Hyla frogs [Dufresnes et al 2015], or green toads [Dufresnes et al 2014]).…”